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| intel opencl optimization guide: OpenCL Programming Guide Aaftab Munshi, Benedict Gaster, Timothy G. Mattson, Dan Ginsburg, 2011-07-07 Using the new OpenCL (Open Computing Language) standard, you can write applications that access all available programming resources: CPUs, GPUs, and other processors such as DSPs and the Cell/B.E. processor. Already implemented by Apple, AMD, Intel, IBM, NVIDIA, and other leaders, OpenCL has outstanding potential for PCs, servers, handheld/embedded devices, high performance computing, and even cloud systems. This is the first comprehensive, authoritative, and practical guide to OpenCL 1.1 specifically for working developers and software architects. Written by five leading OpenCL authorities, OpenCL Programming Guide covers the entire specification. It reviews key use cases, shows how OpenCL can express a wide range of parallel algorithms, and offers complete reference material on both the API and OpenCL C programming language. Through complete case studies and downloadable code examples, the authors show how to write complex parallel programs that decompose workloads across many different devices. They also present all the essentials of OpenCL software performance optimization, including probing and adapting to hardware. Coverage includes Understanding OpenCL’s architecture, concepts, terminology, goals, and rationale Programming with OpenCL C and the runtime API Using buffers, sub-buffers, images, samplers, and events Sharing and synchronizing data with OpenGL and Microsoft’s Direct3D Simplifying development with the C++ Wrapper API Using OpenCL Embedded Profiles to support devices ranging from cellphones to supercomputer nodes Case studies dealing with physics simulation; image and signal processing, such as image histograms, edge detection filters, Fast Fourier Transforms, and optical flow; math libraries, such as matrix multiplication and high-performance sparse matrix multiplication; and more Source code for this book is available at https://code.google.com/p/opencl-book-samples/ |
| intel opencl optimization guide: Intel Xeon Phi Coprocessor Architecture and Tools Rezaur Rahman, 2013-09-26 Intel® Xeon PhiTM Coprocessor Architecture and Tools: The Guide for Application Developers provides developers a comprehensive introduction and in-depth look at the Intel Xeon Phi coprocessor architecture and the corresponding parallel data structure tools and algorithms used in the various technical computing applications for which it is suitable. It also examines the source code-level optimizations that can be performed to exploit the powerful features of the processor. Xeon Phi is at the heart of world’s fastest commercial supercomputer, which thanks to the massively parallel computing capabilities of Intel Xeon Phi processors coupled with Xeon Phi coprocessors attained 33.86 teraflops of benchmark performance in 2013. Extracting such stellar performance in real-world applications requires a sophisticated understanding of the complex interaction among hardware components, Xeon Phi cores, and the applications running on them. In this book, Rezaur Rahman, anIntel leader in the development of the Xeon Phi coprocessor and the optimization of its applications, presents and details all the features of Xeon Phi core design that are relevant to the practice of application developers, such as its vector units, hardware multithreading, cache hierarchy, and host-to-coprocessor communication channels. Building on this foundation, he shows developers how to solve real-world technical computing problems by selecting, deploying, and optimizing the available algorithms and data structure alternatives matching Xeon Phi’s hardware characteristics. From Rahman’s practical descriptions and extensive code examples, the reader will gain a working knowledge of the Xeon Phi vector instruction set and the Xeon Phi microarchitecture whereby cores execute 512-bit instruction streams in parallel. |
| intel opencl optimization guide: High Performance Parallelism Pearls Volume Two Jim Jeffers, James Reinders, 2015-07-28 High Performance Parallelism Pearls Volume 2 offers another set of examples that demonstrate how to leverage parallelism. Similar to Volume 1, the techniques included here explain how to use processors and coprocessors with the same programming – illustrating the most effective ways to combine Xeon Phi coprocessors with Xeon and other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as biomed, genetics, finance, manufacturing, imaging, and more. Each chapter in this edited work includes detailed explanations of the programming techniques used, while showing high performance results on both Intel Xeon Phi coprocessors and multicore processors. Learn from dozens of new examples and case studies illustrating success stories demonstrating not just the features of Xeon-powered systems, but also how to leverage parallelism across these heterogeneous systems. - Promotes write-once, run-anywhere coding, showing how to code for high performance on multicore processors and Xeon Phi - Examples from multiple vertical domains illustrating real-world use of Xeon Phi coprocessors - Source code available for download to facilitate further exploration |
| intel opencl optimization guide: International Conference on Computational and Information Sciences (ICCIS) 2014 , 2014-11-11 The 6th International Conference on Computational and Information Sciences (ICCIS2014) will be held in NanChong, China. The 6th International Conference on Computational and Information Sciences (ICCIS2014)aims at bringing researchers in the areas of computational and information sciences to exchange new ideas and to explore new ground. The goal of the conference is to push the application of modern computing technologies to science, engineering, and information technologies.Following the success of ICCIS2004,ICCIS2010 and ICCIS2011,ICCIS2012,ICCIS2013,ICCIS2014 conference will consist of invited keynote presentations and contributed presentations of latest developments in computational and information sciences. The 2014 International Conference on Computational and Information Sciences (ICCIS 2014), now in its sixth run, has become one of the premier conferences in this dynamic and exciting field. The goal of ICCIS is to catalyze the communications among various communities in computational and information sciences. ICCIS provides a venue for the participants to share their recent research and development, to seek for collaboration resources and opportunities, and to build professional networks. |
| intel opencl optimization guide: Euro-Par 2014: Parallel Processing Fernando Silva, Inês Dutra, Vitor Santos Costa, 2014-08-11 This book constitutes the refereed proceedings of the 20th International Conference on Parallel and Distributed Computing, Euro-Par 2014, held in Porto, Portugal, in August 2014. The 68 revised full papers presented were carefully reviewed and selected from 267 submissions. The papers are organized in 15 topical sections: support tools environments; performance prediction and evaluation; scheduling and load balancing; high-performance architectures and compilers; parallel and distributed data management; grid, cluster and cloud computing; green high performance computing; distributed systems and algorithms; parallel and distributed programming; parallel numerical algorithms; multicore and manycore programming; theory and algorithms for parallel computation; high performance networks and communication; high performance and scientific applications; and GPU and accelerator computing. |
| intel opencl optimization guide: OpenMP: Conquering the Full Hardware Spectrum Xing Fan, Bronis R. de Supinski, Oliver Sinnen, Nasser Giacaman, 2019-08-26 This book constitutes the proceedings of the 15th International Workshop on Open MP, IWOMP 2019, held in Auckland, New Zealand, in September 2019. The 22 full papers presented in this volume were carefully reviewed and selected for inclusion in this book. The papers are organized in topical sections named: best paper; tools, accelerators, compilation, extensions, tasking, and using OpenMP. |
| intel opencl optimization guide: Search Based Software Engineering Federica Sarro, Kalyanmoy Deb, 2016-09-23 This book constitutes the refereed proceedings of the 8th International Symposium on Search-Based Software Engineering, SSBSE 2016, held in Raleigh, NC, USA, in October 2016.The 13 revised full papers and 4 short papers presented together with 7 challenge track and 4 graduate student track papers were carefully reviewed and selected from 48 submissions. Search Based Software Engineering (SBSE) studies the application of meta-heuristic optimization techniques to various software engineering problems, ranging from requirements engineering to software testing and maintenance. |
| intel opencl optimization guide: Data Parallel C++ James Reinders, Ben Ashbaugh, James Brodman, Michael Kinsner, John Pennycook, Xinmin Tian, 2020-11-19 Learn how to accelerate C++ programs using data parallelism. This open access book enables C++ programmers to be at the forefront of this exciting and important new development that is helping to push computing to new levels. It is full of practical advice, detailed explanations, and code examples to illustrate key topics. Data parallelism in C++ enables access to parallel resources in a modern heterogeneous system, freeing you from being locked into any particular computing device. Now a single C++ application can use any combination of devices—including GPUs, CPUs, FPGAs and AI ASICs—that are suitable to the problems at hand. This book begins by introducing data parallelism and foundational topics for effective use of the SYCL standard from the Khronos Group and Data Parallel C++ (DPC++), the open source compiler used in this book. Later chapters cover advanced topics including error handling, hardware-specific programming, communication and synchronization, and memory model considerations. Data Parallel C++ provides you with everything needed to use SYCL for programming heterogeneous systems. What You'll Learn Accelerate C++ programs using data-parallel programming Target multiple device types (e.g. CPU, GPU, FPGA) Use SYCL and SYCL compilers Connect with computing’s heterogeneous future via Intel’s oneAPI initiative Who This Book Is For Those new data-parallel programming and computer programmers interested in data-parallel programming using C++. |
| intel opencl optimization guide: Heterogeneous Computing with OpenCL 2.0 David R. Kaeli, Perhaad Mistry, Dana Schaa, Dong Ping Zhang, 2015-06-18 Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs). This fully-revised edition includes the latest enhancements in OpenCL 2.0 including: • Shared virtual memory to increase programming flexibility and reduce data transfers that consume resources • Dynamic parallelism which reduces processor load and avoids bottlenecks • Improved imaging support and integration with OpenGL Designed to work on multiple platforms, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, this book explores memory spaces, optimization techniques, extensions, debugging and profiling. Multiple case studies and examples illustrate high-performance algorithms, distributing work across heterogeneous systems, embedded domain-specific languages, and will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms. Updated content to cover the latest developments in OpenCL 2.0, including improvements in memory handling, parallelism, and imaging support Explanations of principles and strategies to learn parallel programming with OpenCL, from understanding the abstraction models to thoroughly testing and debugging complete applications Example code covering image analytics, web plugins, particle simulations, video editing, performance optimization, and more |
| intel opencl optimization guide: Performance Optimization Made Simple: A Practical Guide to Programming William E. Clark, 2025-04-17 Performance optimization is a fundamental discipline in modern software development, directly influencing application speed, resource utilization, and the quality of user experience. This book offers a clear and practical exploration of performance optimization, introducing the essential principles, metrics, and methodologies necessary for writing efficient, scalable code. Readers are guided step by step through critical concepts such as execution time, algorithmic complexity, memory management, and input/output efficiency. Structured for clarity and depth, the book systematically examines the impact of data structures, algorithm design, and hardware considerations—including concurrency and parallelism—on program performance. Through real-world examples and actionable techniques, it addresses common pitfalls and provides effective strategies for measuring, analyzing, and improving the responsiveness and efficiency of software systems. Special chapters explore performance trade-offs in energy-constrained environments, the use of compilers and build tools, and balancing optimization with security requirements. This book is intended for students, working programmers, and technical professionals who seek to enhance their understanding of software efficiency. With an emphasis on both foundational concepts and practical application, it equips readers to diagnose performance bottlenecks, apply targeted optimizations, and maintain high standards of software quality throughout the development lifecycle. Whether read sequentially or used as a reference, it provides the essential knowledge required to develop high-performance, maintainable software across a broad range of computing environments. |
| intel opencl optimization guide: Scaling OpenMP for Exascale Performance and Portability Bronis R. de Supinski, Stephen L. Olivier, Christian Terboven, Barbara M. Chapman, Matthias S. Müller, 2017-08-30 This book constitutes the proceedings of the 13th International Workshop on OpenMP, IWOMP 2017, held in Stony Brook, NY, USA, in September 2017. The 23 full papers presented in this volume were carefully reviewed and selected from 28 submissions. They were organized in topical sections named: Advanced Implementations and Extensions; OpenMP Application Studies; Analyzing and Extending Tasking; OpenMP 4 Application Evaluation; Extended Parallelism Models: Performance Analysis and Tools; and Advanced Data Management with OpenMP. |
| intel opencl optimization guide: Design of FPGA-Based Computing Systems with OpenCL Hasitha Muthumala Waidyasooriya, Masanori Hariyama, Kunio Uchiyama, 2017-10-24 This book provides wide knowledge about designing FPGA-based heterogeneous computing systems, using a high-level design environment based on OpenCL (Open Computing language), which is called OpenCL for FPGA. The OpenCL-based design methodology will be the key technology to exploit the potential of FPGAs in various applications such as low-power embedded applications and high-performance computing. By understanding the OpenCL-based design methodology, readers can design an entire FPGA-based computing system more easily compared to the conventional HDL-based design, because OpenCL for FPGA takes care of computation on a host, data transfer between a host and an FPGA, computation on an FPGA with a capable of accessing external DDR memories. In the step-by-step way, readers can understand followings: how to set up the design environment how to write better codes systematically considering architectural constraints how to design practical applications |
| intel opencl optimization guide: High Performance Computing Juan Luis Crespo-Mariño, Esteban Meneses-Rojas, 2020-02-12 This book constitutes the refereed proceedings of the 6th Latin American High Performance Computing Conference, CARLA 2019, held in Turrialba, Costa Rica, in September 2019. The 32 revised full papers presented were carefully reviewed and selected out of 62 submissions. The papers included in this book are organized according to the conference tracks - regular track on high performance computing: applications; algorithms and models; architectures and infrastructures; and special track on bioinspired processing (BIP): neural and evolutionary approaches; image and signal processing; biodiversity informatics and computational biology. |
| intel opencl optimization guide: Heterogeneous Computing with OpenCL Benedict Gaster, Lee Howes, David R. Kaeli, Perhaad Mistry, Dana Schaa, 2012-11-13 Heterogeneous Computing with OpenCL, Second Edition teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. It is the first textbook that presents OpenCL programming appropriate for the classroom and is intended to support a parallel programming course. Students will come away from this text with hands-on experience and significant knowledge of the syntax and use of OpenCL to address a range of fundamental parallel algorithms. Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, Heterogeneous Computing with OpenCL explores memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. It includes detailed examples throughout, plus additional online exercises and other supporting materials that can be downloaded at http://www.heterogeneouscompute.org/?page_id=7 This book will appeal to software engineers, programmers, hardware engineers, and students/advanced students. Explains principles and strategies to learn parallel programming with OpenCL, from understanding the four abstraction models to thoroughly testing and debugging complete applications. Covers image processing, web plugins, particle simulations, video editing, performance optimization, and more. Shows how OpenCL maps to an example target architecture and explains some of the tradeoffs associated with mapping to various architectures Addresses a range of fundamental programming techniques, with multiple examples and case studies that demonstrate OpenCL extensions for a variety of hardware platforms |
| intel opencl optimization guide: OpenCL Programming by Example Ravishekhar Banger, Banger Bhattacharyya, 2013-11 This book follows an example-driven, simplified, and practical approach to using OpenCL for general purpose GPU programming.If you are a beginner in parallel programming and would like to quickly accelerate your algorithms using OpenCL, this book is perfect for you! You will find the diverse topics and case studies in this book interesting and informative. You will only require a good knowledge of C programming for this book, and an understanding of parallel implementations will be useful, but not necessary. |
| intel opencl optimization guide: Intelligent Sustainable Systems Atulya K. Nagar, Dharm Singh Jat, Durgesh Kumar Mishra, Amit Joshi, 2023-01-01 This book provides insights of World Conference on Smart Trends in Systems, Security and Sustainability (WS4 2022) which is divided into different sections such as Smart IT Infrastructure for Sustainable Society; Smart Management Prospective for Sustainable Society; Smart Secure Systems for Next Generation Technologies; Smart Trends for Computational Graphics and Image Modeling; and Smart Trends for Biomedical and Health Informatics. The proceedings is presented in two volumes. The book is helpful for active researchers and practitioners in the field. |
| intel opencl optimization guide: Applied Reconfigurable Computing. Architectures, Tools, and Applications Francesca Palumbo, Georgios Keramidas, Nikolaos Voros, Pedro C. Diniz, 2023-09-15 This book constitutes the proceedings of the 19th International Symposium on Applied Reconfigurable Computing, ARC 2023, which was held in Cottbus, Germany, in September 2023. The 18 full papers presented in this volume were reviewed and selected from numerous submissions. The proceedings also contain 4 short PhD papers. The contributions were organized in topical sections as follows: Design methods and tools; applications; architectures; special session: near and in-memory computing; and PhD forum papers. |
| intel opencl optimization guide: Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU) Hyesoon Kim, Richard Vuduc, Sara Baghsorkhi, Jee Choi, Wen-mei W. Hwu, 2022-05-31 General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. Relative to more traditional multicore systems of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models. We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms. We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques. Table of Contents: GPU Design, Programming, and Trends / Performance Principles / From Principles to Practice: Analysis and Tuning / Using Detailed Performance Analysis to Guide Optimization |
| intel opencl optimization guide: CUDA Application Design and Development Rob Farber, 2011-10-31 The book then details the thought behind CUDA and teaches how to create, analyze, and debug CUDA applications. Throughout, the focus is on software engineering issues: how to use CUDA in the context of existing application code, with existing compilers, languages, software tools, and industry-standard API libraries.--Pub. desc. |
| intel opencl optimization guide: Data Plane Development Kit (DPDK) Heqing Zhu, 2020-11-19 This book brings together the insights and practical experience of some of the most experienced Data Plane Development Kit (DPDK) technical experts, detailing the trend of DPDK, data packet processing, hardware acceleration, packet processing and virtualization, as well as the practical application of DPDK in the fields of SDN, NFV, and network storage. The book also devotes many chunks to exploring various core software algorithms, the advanced optimization methods adopted in DPDK, detailed practical experience, and the guides on how to use DPDK. |
| intel opencl optimization guide: Artificial Intelligence and Soft Computing Leszek Rutkowski, Rafał Scherer, Marcin Korytkowski, Witold Pedrycz, Ryszard Tadeusiewicz, Jacek M. Zurada, 2021-10-05 The two-volume set LNAI 12854 and 12855 constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2021, held in Zakopane, Poland, in June 2021. Due to COVID 19, the conference was held virtually. The 89 full papers presented were carefully reviewed and selected from 195 submissions. The papers included both traditional artificial intelligence methods and soft computing techniques as well as follows: · Neural Networks and Their Applications · Fuzzy Systems and Their Applications · Evolutionary Algorithms and Their Applications · Artificial Intelligence in Modeling and Simulation · Computer Vision, Image and Speech Analysis · Data Mining · Various Problems of Artificial Intelligence · Bioinformatics, Biometrics and Medical Applications |
| intel opencl optimization guide: Intel Xeon Phi Processor High Performance Programming James Jeffers, James Reinders, Avinash Sodani, 2016-05-31 Intel Xeon Phi Processor High Performance Programming is an all-in-one source of information for programming the Second-Generation Intel Xeon Phi product family also called Knights Landing. The authors provide detailed and timely Knights Landingspecific details, programming advice, and real-world examples. The authors distill their years of Xeon Phi programming experience coupled with insights from many expert customers — Intel Field Engineers, Application Engineers, and Technical Consulting Engineers — to create this authoritative book on the essentials of programming for Intel Xeon Phi products. Intel® Xeon PhiTM Processor High-Performance Programming is useful even before you ever program a system with an Intel Xeon Phi processor. To help ensure that your applications run at maximum efficiency, the authors emphasize key techniques for programming any modern parallel computing system whether based on Intel Xeon processors, Intel Xeon Phi processors, or other high-performance microprocessors. Applying these techniques will generally increase your program performance on any system and prepare you better for Intel Xeon Phi processors. - A practical guide to the essentials for programming Intel Xeon Phi processors - Definitive coverage of the Knights Landing architecture - Presents best practices for portable, high-performance computing and a familiar and proven threads and vectors programming model - Includes real world code examples that highlight usages of the unique aspects of this new highly parallel and high-performance computational product - Covers use of MCDRAM, AVX-512, Intel® Omni-Path fabric, many-cores (up to 72), and many threads (4 per core) - Covers software developer tools, libraries and programming models - Covers using Knights Landing as a processor and a coprocessor |
| intel opencl optimization guide: OpenVX Programming Guide Frank Brill, Victor Erukhimov, Radhakrishna Giduthuri, Steve Ramm, 2020-05-22 OpenVX is the computer vision API adopted by many high-performance processor vendors. It is quickly becoming the preferred way to write fast and power-efficient code on embedded systems. OpenVX Programming Guidebook presents definitive information on OpenVX 1.2 and 1.3, the Neural Network, and other extensions as well as the OpenVX Safety Critical standard. This book gives a high-level overview of the OpenVX standard, its design principles, and overall structure. It covers computer vision functions and the graph API, providing examples of usage for the majority of the functions. It is intended both for the first-time user of OpenVX and as a reference for experienced OpenVX developers. - Get to grips with the OpenVX standard and gain insight why various options were chosen - Start developing efficient OpenVX code instantly - Understand design principles and use them to create robust code - Develop consumer and industrial products that use computer vision to understand and interact with the real world |
| intel opencl optimization guide: Languages and Compilers for Parallel Computing James Brodman, Peng Tu, 2015-04-30 This book constitutes the thoroughly refereed post-conference proceedings of the 27th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2014, held in Hillsboro, OR, USA, in September 2014. The 25 revised full papers were carefully reviewed and selected from 39 submissions. The papers are organized in topical sections on accelerator programming; algorithms for parallelism; compilers; debugging; vectorization. |
| intel opencl optimization guide: Structured Parallel Programming Michael McCool, James Reinders, Arch Robison, 2012-07-31 Structured Parallel Programming offers the simplest way for developers to learn patterns for high-performance parallel programming. Written by parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders, this book explains how to design and implement maintainable and efficient parallel algorithms using a composable, structured, scalable, and machine-independent approach to parallel computing. It presents both theory and practice, and provides detailed concrete examples using multiple programming models. The examples in this book are presented using two of the most popular and cutting edge programming models for parallel programming: Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology. Software developers, computer programmers, and software architects will find this book extremely helpful. - The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming models - Develops a composable, structured, scalable, and machine-independent approach to parallel computing - Includes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers |
| intel opencl optimization guide: A New Generation of Cosmic Superstring Simulations José Ricardo C. C. C. Correira, 2023-01-13 Topological defects are an expected consequence of phase transitions in the early Universe. As such these objects, if detected, provide unequivocal evidence of physics beyond the Standard Model. This means they are prime targets for new observational facilities. However, our understanding of defects is heavily bottlenecked by computational limitations. In this book, the author explores the use of accelerator hardware to alleviate this problem, presenting the world’s first (multiple-)GPU defect simulations. Such simulations can evolve a network of line-like cosmic strings at an unprecedented resolution. Then these are used to obtain the most accurate to date calibrations of semi-analytical modelling and to show the impact of accuracy on observational consequences of strings. Lastly, a modified version of this application is used to study interconnected networks of strings in greater detail than ever before. This book benefits any student or researcher who wishes to learn about field theory simulations in the early Universe and about supercomputing with multiple accelerators. |
| intel opencl optimization guide: Intel Xeon Phi Coprocessor High Performance Programming James Jeffers, James Reinders, 2013-02-11 Authors Jim Jeffers and James Reinders spent two years helping educate customers about the prototype and pre-production hardware before Intel introduced the first Intel Xeon Phi coprocessor. They have distilled their own experiences coupled with insights from many expert customers, Intel Field Engineers, Application Engineers and Technical Consulting Engineers, to create this authoritative first book on the essentials of programming for this new architecture and these new products. This book is useful even before you ever touch a system with an Intel Xeon Phi coprocessor. To ensure that your applications run at maximum efficiency, the authors emphasize key techniques for programming any modern parallel computing system whether based on Intel Xeon processors, Intel Xeon Phi coprocessors, or other high performance microprocessors. Applying these techniques will generally increase your program performance on any system, and better prepare you for Intel Xeon Phi coprocessors and the Intel MIC architecture. - A practical guide to the essentials of the Intel Xeon Phi coprocessor - Presents best practices for portable, high-performance computing and a familiar and proven threaded, scalar-vector programming model - Includes simple but informative code examples that explain the unique aspects of this new highly parallel and high performance computational product - Covers wide vectors, many cores, many threads and high bandwidth cache/memory architecture |
| intel opencl optimization guide: CUDA by Example Jason Sanders, Edward Kandrot, 2010-07-19 CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required—just the ability to program in a modestly extended version of C. CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA. http://developer.nvidia.com/object/cuda-by-example.html |
| intel opencl optimization guide: Introducing Windows 10 for IT Professionals Ed Bott, 2016-02-18 Get a head start evaluating Windows 10--with technical insights from award-winning journalist and Windows expert Ed Bott. This guide introduces new features and capabilities, providing a practical, high-level overview for IT professionals ready to begin deployment planning now. This edition was written after the release of Windows 10 version 1511 in November 2015 and includes all of its enterprise-focused features. The goal of this book is to help you sort out what’s new in Windows 10, with a special emphasis on features that are different from the Windows versions you and your organization are using today, starting with an overview of the operating system, describing the many changes to the user experience, and diving deep into deployment and management tools where it’s necessary. |
| intel opencl optimization guide: Parallel Programming for Modern High Performance Computing Systems Pawel Czarnul, 2018-03-05 In view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today, These include multicore CPUs, manycore (co)processors, such as Intel Xeon Phi, accelerators, such as GPUs, and clusters, as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms, such as master-slave, geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed, including MPI, OpenMP, Pthreads, CUDA, OpenCL, and OpenACC. It also demonstrates, through selected code listings, how selected APIs can be used to implement important programming paradigms. Furthermore, it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources, and it shows how to use modern elements of these APIs. Selected optimization techniques are also included, such as overlapping communication and computations implemented using various APIs. Features: Discusses the popular and currently available computing devices and cluster systems Includes typical paradigms used in parallel programs Explores popular APIs for programming parallel applications Provides code templates that can be used for implementation of paradigms Provides hybrid code examples allowing multi-level parallelization Covers the optimization of parallel programs |
| intel opencl optimization guide: Structured Parallel Programming Michael McCool, James Reinders, Arch Robison, 2012-06-25 Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of the most popular and cutting edge programming models for parallel programming: Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology. The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming models Develops a composable, structured, scalable, and machine-independent approach to parallel computing Includes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers |
| intel opencl optimization guide: Hardware Acceleration of Computational Holography Tomoyoshi Shimobaba, Tomoyoshi Ito, 2023-07-17 This book explains the hardware implementation of computational holography and hardware acceleration techniques, along with a number ofconcrete example source codes that enable fast computation. Computational holography includes computer-based holographictechnologies such as computer-generated hologram and digital holography, for which acceleration of wave-optics computation is highly desirable.This book describes hardware implementations on CPUs (Central Processing Units), GPUs (Graphics Processing Units) and FPGAs (Field ProgrammableGate Arrays). This book is intended for readers involved in holography as well as anyone interested in hardware acceleration. |
| intel opencl optimization guide: The CUDA Handbook Nicholas Wilt, 2013 'The CUDA Handbook' begins where 'CUDA by Example' leaves off, discussing both CUDA hardware and software in detail that will engage any CUDA developer, from the casual to the most hardcore. Newer CUDA developers will see how the hardware processes commands and the driver checks progress; hardcore CUDA developers will appreciate topics such as the driver API, context migration, and how best to structure CPU/GPU data interchange and synchronization. The book is partly a reference resource and partly a cookbook. |
| intel opencl optimization guide: Embedded Microprocessor System Design using FPGAs Uwe Meyer-Baese, 2021-03-15 This textbook for courses in Embedded Systems introduces students to necessary concepts, through a hands-on approach. It gives a great introduction to FPGA-based microprocessor system design using state-of-the-art boards, tools, and microprocessors from Altera/Intel® and Xilinx®. HDL-based designs (soft-core), parameterized cores (Nios II and MicroBlaze), and ARM Cortex-A9 design are discussed, compared and explored using many hand-on designs projects. Custom IP for HDMI coder, Floating-point operations, and FFT bit-swap are developed, implemented, tested and speed-up is measured. Downloadable files include all design examples such as basic processor synthesizable code for Xilinx and Altera tools for PicoBlaze, MicroBlaze, Nios II and ARMv7 architectures in VHDL and Verilog code, as well as the custom IP projects. Each Chapter has a substantial number of short quiz questions, exercises, and challenging projects. Explains soft, parameterized, and hard core systems design tradeoffs; Demonstrates design of popular KCPSM6 8 Bit microprocessor step-by-step; Discusses the 32 Bit ARM Cortex-A9 and a basic processor is synthesized; Covers design flows for both FPGA Market leaders Nios II Altera/Intel and MicroBlaze Xilinx system; Describes Compiler-Compiler Tool development; Includes a substantial number of Homework’s and FPGA exercises and design projects in each chapter. |
| intel opencl optimization guide: WebGL Programming Guide Kouichi Matsuda, Rodger Lea, 2013 With this book, students will learn step-by-step, through realistic examples, building their skills as they move from simple to complex solutions for building visually appealing web pages and 3D applications with WebGL. Media, 3D graphics, and WebGL pioneers Dr. Kouichi Matsuda and Dr. Rodger Lea offer easy-to-understand tutorials on key aspects of WebGL, plus 100 downloadable sample programs, each demonstrating a specific WebGL topic. Students will move from basic techniques such as rendering, animating, and texturing triangles, all the way to advanced techniques such as fogging, shadowing, shader switching, and displaying 3D models generated by Blender or other authoring tools. This book won't just teach WebGL best practices, it will give a library of code to jumpstart projects. |
| intel opencl optimization guide: Programming Massively Parallel Processors David Kirk, Wen-mei Hwu, 2021 |
| intel opencl optimization guide: CUDA Programming Shane Cook, 2012-11-13 'CUDA Programming' offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. |
| intel opencl optimization guide: IBM Software-Defined Storage Guide Larry Coyne, Joe Dain, Eric Forestier, Patrizia Guaitani, Robert Haas, Christopher D. Maestas, Antoine Maille, Tony Pearson, Brian Sherman, Christopher Vollmar, IBM Redbooks, 2018-07-21 Today, new business models in the marketplace coexist with traditional ones and their well-established IT architectures. They generate new business needs and new IT requirements that can only be satisfied by new service models and new technological approaches. These changes are reshaping traditional IT concepts. Cloud in its three main variants (Public, Hybrid, and Private) represents the major and most viable answer to those IT requirements, and software-defined infrastructure (SDI) is its major technological enabler. IBM® technology, with its rich and complete set of storage hardware and software products, supports SDI both in an open standard framework and in other vendors' environments. IBM services are able to deliver solutions to the customers with their extensive knowledge of the topic and the experiences gained in partnership with clients. This IBM RedpaperTM publication focuses on software-defined storage (SDS) and IBM Storage Systems product offerings for software-defined environments (SDEs). It also provides use case examples across various industries that cover different client needs, proposed solutions, and results. This paper can help you to understand current organizational capabilities and challenges, and to identify specific business objectives to be achieved by implementing an SDS solution in your enterprise. |
| intel opencl optimization guide: Algorithms and Architectures for Parallel Processing Shadi Ibrahim, Kim-Kwang Raymond Choo, Zheng Yan, Witold Pedrycz, 2017-08-09 This book constitutes the proceedings of the 17th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2017, held in Helsinki, Finland, in August 2017. The 25 full papers presented were carefully reviewed and selected from 117 submissions. They cover topics such as parallel and distributed architectures; software systems and programming models; distributed and network-based computing; big data and its applications; parallel and distributed algorithms; applications of parallel and distributed computing; service dependability and security in distributed and parallel systems; service dependability and security in distributed and parallel systems; performance modeling and evaluation.This volume also includes 41 papers of four workshops, namely: the 4th International Workshop on Data, Text, Web, and Social Network Mining (DTWSM 2017), the 5th International Workshop on Parallelism in Bioinformatics (PBio 2017), the First International Workshop on Distributed Autonomous Computing in Smart City (DACSC 2017), and the Second International Workshop on Ultrascale Computing for Early Researchers (UCER 2017). |
| intel opencl optimization guide: Advances in Distributed Computing and Machine Learning Rashmi Ranjan Rout, Soumya Kanti Ghosh, Prasanta K. Jana, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Kuan-Ching Li, 2022-07-27 This book includes a collection of peer-reviewed best selected research papers presented at the Third International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2022), organized by Department of Computer Science and Engineering, National Institute of Technology, Warangal, Telangana, India, during 15–16 January 2022. This book presents recent innovations in the field of scalable distributed systems in addition to cutting edge research in the field of Internet of Things (IoT) and blockchain in distributed environments. |
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